SPSS统计分析软件基础教程(英文有图示)

An Introduction to SPSS

Or PASW

The two laboratory sessions created for this course introduce students to the use of SPSS software.

Section One

To Should be completed by all students

Section Three

Section Four Further statistical analysis for you to try

It is expected that students should complete the exercises up to and including Section Three within class time, if this is not achieved students should complete the exercises in their own time.

Introduction to SPSS

Section One

Introduction

Section One introduces the various screens and displays as well as explaining how to input

your survey and your data.

SPSS is one of the most popular statistical analysis packages in use today and has been around for well over 20 years. The latest version with the w indow?s interface is particularly easy to use. The windows environment also facilitates the import and export of data, for example importing data from a spreadsheet and exporting results to a word document.

The University holds a license that allows students to have a copy of SPSS on their own computers. The CD for installing the latest version of SPSS can be borrowed from the Library. Starting SPSS

PASW Version 18 is the latest version. It can be

found from Start(Bottom left hand corner),

Programmes, SPSS Inc, PASW 18. The opening

display asks you to select one of a number of

options. At the moment click on the Red Cross to

close the box.

The Opening Display

The window displayed is

called the Data Editor; this is

used for entering, editing and

selecting data. The Data

Editor has two views: the

Variable View and the Data

View you can flip from one

view to the other by using the

tab at the bottom of the page. SPSS has a number of other windows including Output, Help and Tutorial.

Help System

The SPSS Help System is very comprehensive; from the main

menu select Help: a sub menu appears containing:

Help Topics -.Arranged in three ways:

1.Contents give help by general function.

2. Index,gives an alphabetical listing of help topics. Enter a topic, then select a

more specific topic from the list displayed (by highlighting it), click Display. This

gives general information on the topic. SPSS is a very powerful programme and

has a variety of application, so don?t worry about the various topics which will be

meaningless to you at the moment!

3. Search, will find a given word or set of words in help.

Tutorial - step by step tutorials are available on a number of topics.

Statistics Coach

A data set must be loaded in the Data Editor before this option can be used. This

could be data collected for your assignment or from questionnaires used in your dissertation. The statistics coach provides step by step guidance on the analyses that are permissible on the open data set.

Entering Data

The best introduction to entering data in SPSS is to go through the SPSS tutorial on entering data. To do this select: Help, Topic, Entering Data.

Data Editor

Variable View contains descriptions of the attributes of each variable in the data file. In Variable View:

? Rows are variables.

? Columns are variable attributes.

(For example: if you have produced a questionnaire each row represents a question or part of a question from your questionnaire.)

1 2 3 4 5 6 7 8 9 10 11

You can add or delete variables and modify attributes of variables, including the following attributes:

1. Name-This is the name you allocate to the variable

Variable names:

?Must be unique

?Can only have eight or less characters

?Must begin with a letter (not a number)

?Cannot include full stops, blanks or other characters (!, ?, @, etc); and

?Cannot include word used as commands by SPSS (all, ne, eq, to, le, It, by, or, gt, and, ge, with)

NB The first variable in any data set should be ID, which is a unique number that identifies each case. Before beginning that data entry process, go through and assign a number to each of your questionnaires or data records. Write the number clearly on the front cover. Later, if you find an error in the data set, having the questionnaires or data records numbered will allow you to check back and find where the error occurred.

2. Type-the variable type defaults as numeric, leave it as this unless changing to

currency (see later).

3. Width- The number of characters displayed. The default here is 8, it is normally

not necessary to change it.

4. Decimals-The number of decimal places displayed, the default here is two.

5. Label-Allows for a more detailed description of the Name.

6. Values-Values are code numbers applied to a stringed response

7. Missing Values- defines specified data values as user-missing. For example,

you might want to distinguish between data that are missing because a

respondent refused to answer and data that are missing because the question

didn't apply to that respondent. Data values that are specified as user-missing are

flagged for special treatment and are excluded from most calculations.

8. Columns- Simply the width of the columns: defaults at 8.

9. Align- The position of text within the column: defaults to the right.

10. Measure- You can specify the level of measurement as scale (numeric data on

an interval or ratio scale), ordinal, or nominal.

?Nominal. A variable can be treated as nominal when its values represent

categories with no intrinsic ranking (for example, the department of the

company in which an employee works). Examples of nominal variables

include region, zip code, and religious affiliation.

?Ordinal.A variable can be treated as ordinal when its values represent

categories with some intrinsic ranking (for example, levels of service

satisfaction from highly dissatisfied to highly satisfied). Examples of ordinal

variables include attitude scores representing degree of satisfaction or

confidence and preference rating scores.

?Scale. A variable can be treated as scale when its values represent ordered

categories with a meaningful metric, so that distance comparisons between

values are appropriate. Examples of scale variables include age in years and

income in thousands of pounds.

11. Role -Some dialogs support predefined roles that can be used to pre-select

variables for analysis. When you open one of these dialogs, variables that meet

the role requirements will be automatically displayed in the destination list(s).

Available roles are:

Input. The variable will be used as an input (e.g., predictor, independent variable).

Target. The variable will be used as an output or target (e.g., dependent variable).

Both. The variable will be used as both input and output.

None. The variable has no role assignment.

Partition. The variable will be used to partition the data into separate samples for

training, testing, and validation.

By default, all variables are assigned the Input role.

All of these attributes are saved when you save the data file.

Data View

The variables defined in Variable View as rows are transferred in the Data View as columns. Data View is where you input your responses to your survey etc. Each row represents one respondent.

The screen above depicts the variable attributes as values; this

can be changed to value labels by selecting View, and Value

Labels.

Preparing a Codebook

Before you can enter the information from a questionnaire into SPSS you need to prepare a …codebook?. This is in effect a summary of the instructions you will use to convert the information obtained from each questionnaire response into a format that SPSS can understand. Preparing a codebook involves deciding (and documenting) how you will go about:

?Defining and labelling each of the responses to the questions in your questionnaire (variables); and

?Assigning numbers to each of the possible responses.

All this information should be recorded in a book or computer file. Keep this somewhere safe, there is nothing worse than coming back to a data file, which you may have not used for a while, and wondering what the abbreviations and numbers refer to. In your code book you should list all of the variables used in your questionnaire, the abbreviated variable names that you will use in SPSS and the way in which you will code the responses.

Coding Responses

Each response must be assigned a numerical code before it can be entered into SPSS. Variable responses which are already in numerical format i.e. age in years, do not require to be coded, other variables such as gender will need to be converted to numbers (1 = males, 2 = females). If you have used numbers in your questions to label your responses this is relatively straightforward. If not decide on a convention and stick to it. For example, code the first response as 1, the second as 2 and so on.

To code responses to the question above: if a person ticked single they would be coded as 1; if in a relationship, they would be coded 2; if married, 3; and if divorced, 4.

Table 1 below indicates an example of a possible code book for a questionnaire.

Coding Open-ended Questions

For open-ended questions (where respondents can provide their own answers), coding is slightly more complicated. Take for example the question: what is the major source of stress in your life at the moment? To code responses to this you will need to scan through the questionnaire and look for common themes, (e.g.) work, finance, relationships, health or lack of time might be highlighted a number of times. In your codebook you would list these major groups of responses under the variable stress, and assign a number to each (work = 1, finance = 2, relationships = 3 and so on). You may also need to add another numerical code for responses that did not fall into these listed categories (other = 9). When entering that data for each respondent you compare their response with those listed in your codebook and enter the appropriate number into the data set under the variable stress.

Job Survey Parts 1 and 2 Exercises

Throughout the SPSS sessions we will be referring to the Job Survey. In Part 1 the questionnaire targets employees of a local organisation; in Part 2 the questionnaire targets supervisors of the same employees.

Exercise 1.1: Coding the Survey

On the Job Survey questionnaire sheet (See Appendix 1.1), in the allocated space, assign codes to the possible responses.

Exercise 1.2: Entering the Survey into a Blank Data Sheet

If restarting SPSS, select Type in Data and ensure the Data Editor is showing Variable View.

Enter each question from the Survey into

Data Editor.

Start by allocating an Identification Number to

each respondent, enter the variable Name as

ID, change the Decimals to0, and leave all

other columns at the default settings. See

Appendix 1.2 for variable names

Continue on to row 2 with Question 1 in the survey; the variable name will be Ethnicity, change the Decimals to 0. Add the coded values by clicking in the values cell (on the appropriate row) and click on the grey box which will appear. Type 1 for the value and White/European for the value label, and then click ADD, continue until all variable attributes are completed, click OK. Finally, change Measure to Nominal as this is categorical data but is not ranked.

Continue to enter all of the

questions from the

questionnaire.

Exercise 1.3: To Change the Format

Currency Format

Question 3 in the survey asks about salary. We can change the format of this data to currency

format i.e. all data relating to the information will

be prefixed with the ￡ sign. To define currency in

the Type column click on the grey box, select

Custom Currency, CCA, and change to 0

decimal places.

Continue to enter all of the questions from the

questionnaire.

Exercise 1.4: To Input Responses into the Data Editor

To input the responses to the questionnaire ensure the Data Editor is showing Data View. To allow you to practice doing this refer to Appendix 1.3. Appendix 1.3 is an extract of responses given to the Job Survey up to Question 6d. Input these responses into Data View.

Missing Values

One of the most common problems encountered with using questionnaires is that some questions are not fully answered. These gaps in your questionnaire are called missing values or missing data. If this occurs you have to think why the questions have not been answered and what you can do about it. There are four possibilities why this might happen: ?The question did not apply to the respondent

?The respondent refused to answer this particular question

?The respondent did not know the answer

?The respondent simply forgot to answer the question

If whilst inputting your data you find you have missing values, go back to Variable View

and at the appropriate variable, click on the box to the left of the Missing Value cell and select as below.

For the purposes of this survey all missing values will

be coded as 0, with the exception of Absence which

will be coded 99.

Remember to SAVE your work to My Documents.

Introduction to SPSS

Section Two

Introduction

Section Two explains how to view, manipulate, display and describe your data.

Exercise 2.1: To load SPSS

Start, Programs, SPSS.

Click Cancel on the dialogue box to remove it, you are then left with the Data Editor.

Data Editor has a menu bar with many options, as shown below, these include:

File: Used to access any files whether you want to Open an existing SPSS file or read data from another application such as Excel or dBase, or start a New file. It is also the menu option you choose to Save files.

Edit: Can be used to alter data or text in the Data View or the Variable View.

View: Used to alter the way your screen looks. Please leave this on the default settings. Data: Used to define variables and make changes to the data file you are using. Transform: Used to make changes to selected variable(s) in the data file you are using. This can include recode(ing) existing variables and compute(ing) new variables.

Analyze:Used to undertake a variety of analyses such as producing Reports, calculating Descriptive Statistics such as Frequencies and Crosstabs(cross tabulations) and associated summary statistics, as well as various statistical procedures such as Regression and Correlation.

Graphs: Used to create a variety of graphs and charts such as Bar, Line and Pie charts. Utilities:Is for more general housekeeping such as changing display options and fonts, displaying information on variables.

Add-ons: Includes services available such as statistical help.

Window: Operates in the same way as other Windows packages.

Help:A context sensitive help feature which operates the same way as other Windows packages.

Exercise 2.2: To load a previously created SPSS for Windows data file

SPSS for Windows saves data files using a filename of up to 8 characters and the file extension .SAV, for example job survey.sav

In the Menu Bar click on the following:

File (main menu bar), Open (in File menu), exchange on Wide (X:), Data, IB04

A dialogue box similar to that below will appear:

Open the file by clicking on JOB SURVEY and then on the button (or double click on the file name).

You will now see the file appear in the Data View and the filename above the menu bar change to JOB SURVEY.SAV SAVE this file to H:drive and open the file from H:drive for use in today?s session. (Exchange on Wide is a shared network; therefore you can not change and save to this network).

Exercise 2.3: To undertake a frequency distribution

It is always a good idea to “eyeball” your data; this can be done using Frequencies.

?Click on Analyse, Descriptive Statistics, Frequencies

?Opens the Frequencies dialogue box.

?Highlight ethnicity in the left hand box by clicking on it

?Click on the button to move ethnicity into the Variable(s) box

(Note how the arrow button changes direction and the cursor moves to the Variable(s) box. This is to allow you to reverse your decision if you wish.)

?Click on OK

You will now see a series of tables displayed in the SPSS Output Viewer. Note how SPSS first tells you if there are any missing cases. For this variable there are no missing cases.

?Use the and arrows to scroll down and across to view the actual frequencies table. Note how SPSS lets you know if there are any missing cases

and calculates the valid percent appropriately. The valid percentages take

account of any missing values. If they were none then the percent and valid

percent would be the same.

?Repeat this process using Analyze, Descriptive Statistics, Frequencies for Income and Age. You can do this by pointing and clicking on the menu

commands which are visible at the top of your screen.

Whilst you are doing this explore the effect of the

button on your output.

?To remove the variables from the right Variable(s)box within the dialogue box either:

click on the button

or highlight the variable in the right Variable(s) box and click on the button ?To quit this analysis (for example if you make a mistake) click on the button

You may (or may not!) have noticed that each of the tasks you have performed in SPSS have been automatically appended to the SPSS Output Viewer. You can see this by scrolling through your output window using the up and down arrows on the right of the window.

You can edit the SPSS Output Viewer and save it, or parts of it, to a file which can subsequently be read into a word processor. SPSS output files are suffixed with .spv. Alternatively you can print it out directly.

TIP

?To delete some output in the SPSS Output Viewer:

click on the area you want to delete, a line will appear around it.

press the delete key on the keyboard

To delete all the output in the SPSS Output Viewer:

Ensure that the SPSS Output Viewer window is maximised

In the SPSS Output Viewer click on Edit, Select, All, press the delete key on the keyboard

Exercise 2.4: To save the Output

To save the contents of the SPSS Output Viewer to a file

Ensure that the SPSS Output Viewer window is maximised

Click on File, Save as

Type in the filename you wish to save it to in the File name box, making sure the file type is *.spv

Ensure that the file is being saved to the correct drive and directory (i.e. H:drive)

NB Donot close without saving or you will loose all of your output. The Output viewer works like a scroll, each new analysis is added to the end of the previous analysis.

Exercise 2.5: To produce charts

?Click on Graphs, Chart Builder (If a dialogue box appears click okay).

?Select Simple bar graph by clicking on it and dragging to the canvas.

?Then click on and grab ethnicity from the column of variables, onto the x-axis

?Click OK

Your graph will now appear in the Output Viewer.

?Double click on the bar chart and a smaller box appears entitled chart editor.

?Click on one of the bars, all of the bars should now be highlighted with a blue line.

?From the Properties box select Fill and Border; change the colour of your bars.

?Click on Elements, then show data labels.

?In the Properties box, you can add/remove things from the area marked display from the box marked not displayed which are then added to your graphic by

using the red cross to remove and the green arrow to add. Add percentages to

your data labels.

Exercise 2.6: To produce a clustered bar chart

It may make more sense to compare two groups, for

example men and woman. A clustered bar chart will show this.

?Click on Graphs

?Click on Chart Builder.

?Click Bar and Drag the Cluster bar chart icon to the canvas

?Drag Ethnicity from the Variables list to the X-axis and Gender to Cluster on X: set colour

?As the two groups male and female are not of equal numbers, 39 men: 31 women, it would give a more accurate comparison to change Count to Percentage. In the Element Properties box, under Statistic, use the arrow to find percentage.

?Click Apply

?Click Ok

?In Chart Editor show the Percentage Data Labels

?Under Number Format, change the decimal places to 0

Exercise 2.7: Produce a Stacked Bar

?Produce a Stacked Bar variation of the above chart

Exercise 2.8: To produce a pie chart

?Click on Graphs

?Click on Chart Builder.

?From Gallery select Pie/Polar

?Drag the Pie chart icon onto the canvas

?Drag Ethnicity to the x-axis from the variables list

?Change Count to Percentage on the y-axis (Element Properties, Statistics)

?Click Apply

?Click OK

Your Pie chart will now appear on the Output Viewer.

Exercise 2.9: To present your graph in Word

?Open Microsoft Word.

?Select one of the graphs you have produced in the Output Viewer and give it a title.

?Click on the icon circled below or Options, Title

?Give your graph a suitable title

?Close Chart Editor

Your chart with a title should have a box around it, if not click on your chart.

?Right click on your chart and select Copy.

?Paste your chart into your open Word document

?Give your chart a numbered title by selecting Insert, Reference, Caption, decide on position and click OK.

?Immediately after the Figure number, title your chart again.

?Adjust the size of your chart by clicking on it and manipulating the black boxes at the corners.

Figure 1 Ethnicity of Respondents by Gender

Exercise 2.10: To recode variables

When a variable is a scale measure such as at the interval/ratio level, it normally has to be grouped to be presented as a frequency table. Income from the Job Survey is such a variable. To examine the data:

?Click on Analyse, Descriptive Statistics, Frequencies, select Income and click on the Blue Arrow (income should appear in the variables box)

?Select Statistics, select Minimum and Maximum, press Continue then OK

Output Viewer displays the data for Income, you can see the minimum income is ￡11800 and the maximum is ￡21000, and there are thirty-three different categories which are too many to produce a meaningful chart or table. We must, therefore reduce the amount of categories by grouping them. Six new categories seems a useful number. To do this we must Recode the data and give the income category a new variable name called incomegp (income group).

?Transform, Recode,

Variables (opens

Recode into Different

Variables box)

?Select Income and

place in the Numeric

Variables… box

?Type Incomegp into

Name

?Select Change

?Select Old and New

Values (opens Old and

New Values box)

System or User

Missing and under New

Value select System

Missing, select Add

?Select Range:Lowest

through and type

11999, under New

Value type1, select

Add

?Select Range and type

12000 and through and

type13999, under New

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Casewise diagnostics默认；接着选择Model fit、Collinearity diagnotics；点击Continue. 3.点击右侧Plots，选择*ZPRED（标准化预测值）作为纵轴变量，选择DEPENDNT（因变量）作为横轴变量；勾选选项组中的Standardized Residual Plots（标准化残差图）中的Histogram、Normal probability plot；点击Continue.

SPSS统计分析教程独立样本T检验

独立样本T检验 下面我们要用SPSS来做成组设计两样本均数比较的t检验，选择Analyze==>Compare Means==>Independent-Samples T test，系统弹出两样本t检验对话框如下： 将变量X选入test框内，变量 group选入grouping框内，注意这时 下面的Define Groups按钮变黑，表示 该按钮可用，单击它，系统弹出比较组 定义对话框如右图所示： 该对话框用于定义是哪两组相比，在两 个group框内分别输入1和2，表明是 变量group取值为1和2的两组相比。 然后单击Continue按钮，再单击OK 按钮，系统经过计算后会弹出结果浏览 窗口，首先给出的是两组的基本情况描 述，如样本量、均数等（糟糕，刚才的 半天工夫白费了），然后是t检验的结 果如下： Levene's Test for Equality of Variances t-test for Equality of Means F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Lower Upper X Equal variances .032 .860 2.524 22 .019 .4363 .1729 7.777E-02 .7948

差是否齐，这里的戒严结果为F = 0.032，p = 0.860，可见在本例中方差是齐的；第二部分则分别给出两组所在总体方差齐和方差不齐时的t检验结果，由于前面的方差齐性检验结果为方差齐，第二部分就应选用方差齐时的t检验结果，即上面一行列出的t= 2.524，ν=22，p=0.019。从而最终的统计结论为按α=0.05水准，拒绝H0，认为克山病患者与健康人的血磷值不同，从样本均数来看，可认为克山病患者的血磷值较高。

SPSS教程中文完整版

SPSS统计与分析 统计要与大量的数据打交道，涉及繁杂的计算和图表绘制。现代的数据分析工 作如果离开统计软件几乎是无法正常开展。在准确理解和掌握了各种统计方法原理 之后，再来掌握几种统计分析软件的实际操作，是十分必要的。 常见的统计软件有SAS，SPSS，MINITAB，EXCEL 等。这些统计软件的功能和作用大同小异，各自有所侧重。其中的SAS 和SPSS 是目前在大型企业、各类院校以及科研机构中较为流行的两种统计软件。特别是SPSS，其界面友好、功能强大、易学、易用，包含了几乎全部尖端的统计分析方法，具备完善的数据定义、操 作管理和开放的数据接口以及灵活而美观的统计图表制作。SPSS 在各类院校以及科研机构中更为流行。 SPSS（Statistical Product and Service Solutions,意为统计产品与服务解决方案）。自20 世纪60 年代SPSS 诞生以来，为适应各种操作系统平台的要求经历了多次版本更新，各种版本的SPSS for Windows 大同小异，在本试验课程中我们选择PASW Statistics 18.0 作为统计分析应用试验活动的工具。 1．SPSS 的运行模式 SPSS 主要有三种运行模式： （1）批处理模式 这种模式把已编写好的程序（语句程序）存为一个文件，提交给[开始]菜单上[SPSS for Windows]→[Production Mode Facility]程序运行。 （2）完全窗口菜单运行模式 这种模式通过选择窗口菜单和对话框完成各种操作。用户无须学会编程，简单 易用。 （3）程序运行模式 这种模式是在语句（Syntax）窗口中直接运行编写好的程序或者在脚本（script）窗口中运行脚本程序的一种运行方式。这种模式要求掌握SPSS 的语句或 脚本语言。本试验指导手册为初学者提供入门试验教程，采用“完全窗口菜单运行模式”。 2．SPSS 的启动 （1）在windows[开始]→[程序]→[PASW]，在它的次级菜单中单击“SPSS 12.0 for Windows”即可启动SPSS 软件，进入SPSS for Windows 对话框，如图1.1， 图 1.2 所示。

SPSS统计分析方法及应用教学大纲

《SPSS统计软件》课程教学大纲 一、说明 （一）课程定义： 本课程是网络与新媒体专业的选修课程。SPSS统计软件应用课程，是以计算机科学为支持，将统计软件为运用工具，用所学习的统计学理论与方法为指导，系统介绍对社会经济现象数据的搜集、整理、分析等综合技能。 开设本门课程，能更好的帮助学生理解和掌握统计学的理论及方法，注重学生的实际操作与应用能力的培养。通过该课程的学习，使学生掌握spss统计软件，为其以后的学习和工作打好基础。 （二）编写依据： 本课程大纲根据武汉体育学院体育科技学院人文社科系网络与新媒体专业人才培养方案（2018版）编写。 （三）目的任务： 通过SPSS软件实验教学，培养学生根据实际问题建立SPSS数据文件、利用SPSS软件提供的各种统计功能进行数据的整理与分析，并结合相关的专业知识对分析结果给出解释，为学生以后的工作打下坚实的基础。要求学生课前做好实验准备，课中积极接受和沟通，课后认真总结并写好实验报告。 （四）学时数与学分数： 本课程教学总学时为36课时,2学分。具体学时分配参照下表。 （五）适用对象： 网络与新媒体专业大三学生。 （六）课程编码： KY1810A01

二、教学内容与学时分配 三、教学内容与知识点 第一章SPSS统计分析软件概述 第一节SPSS使用基础 知识点：SPSS软件的基本窗口、退出。 第二节 SPSS的基本运行方式 知识点：窗口菜单方式、程序运行方式、混合运行方式。第二章SPSS数据文件的建立和管理 第一节 SPSS数据文件 知识点：SPSS数据文件的特点、基本组织方法。 第二节 SPSS数据的结构和定义方法